Coupled modelling of sugarcane supply planning and logistics as a management tool

Gal, P.-Y. Le; Masson, Julien Le; Bezuidenhout, C. N.; Lagrange, Louis

doi:10.1016/j.compag.2009.05.006

Cited by 27 publications

(15 citation statements)

References 29 publications

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“…Notwithstanding its non-linearity, in a recent study [2], a basic version of the quality risk management problem (1)- (15) have been discussed and solved via an equivalent linear mixed integer reformulation jointly with scenario based approaches. Also, the authors have been introduced a new (1 − α)−scenario pertinence in order to handle efficiently the probabilistic constraints (4) and to reduce the computational time.…”

Section: Optimization Modulementioning

confidence: 99%

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A Decision Support System for Efficient Crop Production Supply Chain Management

Borodin

Bourtembourg²,

Hnaien

et al. 2014

Computational Science and Its Applications – ICCSA 2014

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Abstract. This paper presents a decision support system for efficient and responsive crop production supply chain management, which captures harvesting, transportation and storage activities, through taking a holistic perspective as a whole. Crop production represents one of the most significant stage in agricultural sector for both agricultural cooperatives and individual farmers, due to its high cost and considerable impact on crop quality and yield. Whilst considering the dynamic behaviour and the intricacy of the studied agricultural system, combined discrete event simulation and optimization approaches, scenario analysis and performance measurement tools are implemented for supporting decision making for cooperatives and individual farmers, respectively. Likewise, it enables to examine and evaluate alternative system re-configurations and strategies for an eventual supply chain rethinking or redesign. The decision support system proves to be particularly responsive and effective when applied to a real life agricultural case study.

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Section: Optimization Modulementioning

confidence: 99%

“…There is extensive literature focusing on many decision-making problems arising from complex agricultural processes and operations that are described by using simulation modelling and improved via the sensibility or scenario-based analysis [1,15,21,22,23].…”

Section: Research Backgroundmentioning

confidence: 99%

A Decision Support System for Efficient Crop Production Supply Chain Management

Borodin

Bourtembourg²,

Hnaien

et al. 2014

Computational Science and Its Applications – ICCSA 2014

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“…Changes concern widely encountered agricultural practices, such as diversification of crop rotations with forage crops, forage production with cover crops (for local livestock), manure spreading on crop fields, and integration of local grain into animal diets (Table 1). They can easily be addressed with available DSS, such as crop models (Rodriguez et al 2014), animal nutrition models (INRA 2007), farm models (Martin et al 2013), and logistics models at the level of local economic organization such as agricultural cooperatives (Le Gal et al 2009). Therefore, no specific DSS needs to be developed for local coexistence.…”

Section: Dss Requirements To Support Complementarity and Synergy Formmentioning

confidence: 99%

“…The greater the transfer distance, the denser products must be in energy, protein, or DM to make the transfer sustainable. Therefore, the logistics involved in crop-livestock integration beyond the farm level must be modeled and simulated (Le Gal et al 2009), for instance using energy accounting (Vigne et al 2013) that converts energy, biophysical, and human resources involved in a given process into equivalents of a single form of energy, usually solar.…”

Section: Spatial Upscalingmentioning

confidence: 99%

Crop–livestock integration beyond the farm level: a review

Martin

Moraine

Ryschawy

et al. 2016

Agron. Sustain. Dev.

142

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Paradoxically, the number of crop-livestock farms is declining across Europe, despite the fact that crop-livestock farms are theoretically optimal to improve the sustainability of agriculture. To solve this issue, crop-livestock integration may be organized beyond the farm level. For instance, local groups of farmers can negotiate land-use allocation patterns and exchange materials such as manure, grain, and straw. Development of such a collective agricultural system raises questions, rarely documented in the literature, about how to integrate crops and livestock among farms, and the consequences, impacts, and conditions of integrating them. Here, we review the different forms of crop-livestock integration beyond the farm level, their potential benefits, and the features of decision support systems (DSS) needed for the integration process. We identify three forms of crop-livestock integration beyond the farm level: local coexistence, complementarity, and synergy, each with increasingly stronger temporal, spatial, and organizational coordination among farms. We claim that the forms of integration implemented define the nature, area, and spatial configuration of crops, grasslands, and animals in farms and landscapes. In turn, these configurations influence the provision of ecosystem services. For instance, we show that the synergy form of integration promotes soil fertility,

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“…Their study shows that an integrated system comprising the harvest, transport, and mill process can lead to significant reductions in delay times and cost. Le Gal et al (2009) develop a simulation to investigate the impact of increased mechanization of the sugarcane harvest. Lejars et al (2008) also develop a simulation model to see the effects of centralized decision-making among the various stakeholders (sugar cane growers, harvesters, haulers, and millers) in the South African industry versus decentralized decision-making.…”

Section: Literature Reviewmentioning

confidence: 99%

Sugarcane Harvest Logistics in Brazil

Lamsal

Jones

Thomas

2017

Transportation Science

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Sugar mills in Brazil represent significant capital investments. To maintain appropriate returns on their investment, sugar companies seek to run the mills at capacity over the entire nine months of the sugarcane harvest season. Because the sugar content of cane degrades considerably once it is cut, maintaining inventories of cut cane is undesirable. Instead, mills want to coordinate the arrival of cut cane with production. In this paper, we present a model of the sugarcane harvest logistics problem in Brazil. We introduce a series of valid inequalities for the model, introduce heuristics for finding an initial feasible solution, and for lifting the lower bound. Computational results demonstrate the effectiveness of the inequalities and heuristics. In addition, we explore the value of allowing trucks to serve multiple rather than single locations and demonstrate the value of allowing the harvest speed to vary.

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Coupled modelling of sugarcane supply planning and logistics as a management tool

Cited by 27 publications

References 29 publications

A Decision Support System for Efficient Crop Production Supply Chain Management

A Decision Support System for Efficient Crop Production Supply Chain Management

Crop–livestock integration beyond the farm level: a review

Sugarcane Harvest Logistics in Brazil

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